Target Selection Algorithm for ADAS Applications
Nirban Saha, Miit Prajapati, Abhisha Chauhan · 2024
Automotive safety and rider comfort have been enhanced by the introduction of the ADAS application in vehicles. Radar-based ADAS solutions are popular due to their detection robustness against weather conditions. Accurate and timely identification of potential collision-causing vehicles is extremely important for safe vehicle operations. However, radar-based ADAS solutions are also prone to false detections caused by multi-path reflections from different reflecting surfaces. To address this issue, this paper presents a time-effective target selection strategy that selects the most potential collision threat vehicle and also eliminates false detections at the same time. Validation of strategy has been performed using simulations involving the front and rear mounting positions of the radar in different driving scenarios.